International Journal of Trend in Scientific
Research and Development (IJTSRD)
International Open Access Journal
ISSN No: 2456 - 6470 | www.ijtsrd.com | Volume - 2 | Issue – 3
Vehicle Density Based Traffic Control System
Anand Gaikwad, Shreya, Shivani Patil
BE Student,
tudent, Department of Electronics and
nd Telecommunication,
Telecommunication
Sinhgad Academy oof Engineering, Kondhwa, Pune, Maharashtra, India
ABSTRACT
In this paper, we proposed a system i.e. vehicle
density based traffic management system. Present day
traffic signal system is fixed time based which may
render inefficient if one lane is operational than the
others. To optimize this problem we have made a
framework for an intelligent traffic control system.
Sometimes higher traffic density at one side of the
junction demands longer green time as compared to
standard allotted time. Basically, it is divided into two
modules. In first module, the timing of si
signal will
change automatically on sensing the traffic density at
any junction. We, therefore propose here a
mechanism in which the time period of green light
and red light is assigned on the basis of the density of
the traffic present at that time. And in second module,
to reduce the crime we develop a technique of
automatic number plate recognition using image
processing. In this paper, the first section is
introduction, second section is literature survey, third
section is block diagram and components, fo
fourth
section is prototype implementation, fifth section is
conclusion, sixth section is references. whatever the
result is shown in this paper is partially executed.
Keywords:: Vehicle Density , Traffic , Signal
I. Introduction
Now-a-days
days conventional traffic light system is based
on fixed time concept allotted to each side of the
junction which cannot be varied as per varying traffic
density [1]. This causes wastage of time and traffic
congestion. The major cause of traffic jamm
jamming is the
more number of vehicle which is caused by the over
growing population. And another problem is that,
traffic police has to keep concentration on vehicles
every day and at every time. The accuracy to catch the
appropriate criminal on the spot is very
ery rarer by traffic
police. The signal timing changes automatically on
sensing the traffic density at the junction.
Most of the work detects edge of the vehicles and
counts the number of traffic on the road. With the
help of dedicated algorithm, morphology
morpho
and image
needed to avoid traffic congestion Also we have used
ANPR which is an image processing technology used
to store the images captured by the cameras as well as
the text from the number plate [2].Thus, we have
designed a framework for a dynamic and automatic
traffic light control system and developed a
simulation based model with codes in to help build
the system. In this, we propose three approaches. In
the first approach - to take data or input from camera.
In the second approach - to process the input data
using ARM processor and finally display it on the
traffic light signal to control the Closed Loop System.
We are proposing such a system that compact with
such kind of problem by automatically switching the
signal by calculating the time at which the vehicles
inwards at stop line.
The traffic lights that are in widespread use today do
not do much complex reasoning when deciding when
to change the lights for the various road users waiting
in different lanes. How long the signal stays green in
one lane and red in another is most often determined
by simple timing that is calculated when the crossing
is designed. Even though today’s methods are robust
and work well when the traffic load is distributed
evenly across the lanes in the intersection, the systems
are very inefficient because they are unable to handle
various simple situations that arise throughout the
day. Unnecessary waiting time in the signal can be
avoided by determining in which side the green signal
should be large during the traffic.
traff The proposed work
@ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 3 | Mar-Apr
Apr 2018
Page: 511
International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470
is to develop a system to recognize the vehicle
number plate and retrieve the owner information from
the database. It is based on inputting a vehicle number
plate image to the system, which recognizes the
characters of vehicle number plate. It matches the
number plate with the respective data and then send
the message to the owner of vehicle, whoever breaks
the rule. The system we propose identify the density
of traffic on individual lanes and thereby regulate the
timing of the signals’ timing and controls the crime.
Calculation” - International Journal on Recent and
Innovation Trends in computing and communication,
Volume: 3 Issue: 2 (ISSN: 2321-8169), September
,2014. The Traffic Management System using Density
Calculation and Emergency Vehicle Alert, track
traffic density at intersection using Road Side Unit
(RSU) and Traffic Control Unit (TCU) will decide the
timing of the traffic signal.
III. Block diagram and components
II. Literature Survey
In the recent past, researchers have tested a wide array
of technologies in an attempt to find improved
methods of monitoring traffic conditions. A brief
survey of technologies explored during the past
decade and a half is given below to provide an
understanding of the level of research interest in
traffic surveillance technologies.
[1] R.B.Jayanthi Rajee, V. Devika, M. Abarna, A.
Aswini Priya –“Traffic Management System using
Image Processing and ARM Processor”- International
Journal of Computer Systems (ISSN: 2394-1065),
Volume 02– Issue 03, March, 2015.In this paper
Image Processing technique used for traffic
management system. Video sensors are used to
capture the image sequences. Using Fuzzy constraint
satisfaction methodology (FCM) the best time for
traffic signal is calculated .This output is given to the
ARM processor and the LED of the traffic signal is
changed based on the ARM processor output.
[2] A Ranganath, T Sree Valli “ INTELLIGENT
MANAGEMENT SYSTEM FOR DENSITY BASED
CONTROL, STOLEN VEHICLE AND AUTO
CLEARANCE ”- International Journal of Advanced
Technology in Engineering and Science, vol no.3Issue 08, August,2015. This paper proposed an
advanced intelligent traffic control system. This
system was implemented based on present criteria that
tacking two condition in those one is heavy traffic
control and another one is making a root for
emergency vehicle like ambulance and VIP vehicle. A
sensor network work is used to detect the traffic
density, stolen vehicle and a RF based communication
system for getting information from the emergency
vehicle. To identify the stolen vehicle, RFID
technology is used.
[3] Farheena Shaikh, Naisha Taban Khan, Saima
Zareen Ansari “Controlling Traffic Light Signals to
Implement Traffic Scheduling Using Density
The ARM7TDMI-S is a general purpose 32-bit
microprocessor, which offers high-performance and
very low power consumption. This microcontroller
used to make reliable in each component used in this
project. When the signal gets RED then automatically
the Piezo sensor should get activated, piezo sensor is
connected with LPC 2138. The Timer is applied to
signal for the proper orientation between each red and
green signal. Signal 1,2,3,4 are interfaced with
microcontroller, by using proper time the signals get
activated one after another.
We have used Web Camera for this project. The use
of camera is to capture the image of vehicle on
pressure sense by the PIEZO sensor .Web camera is
connected to Base station. The Resolution of this
camera is MJPG_640X180. GSM is global system of
mobile, by using GSM we can make communication
between user and RTO office via wireless
communication .
GSM is used for communication purpose. GSM
interface with one base station to other base station. In
this project we use GSM system for communication
between RTO office to user mobile station. The basic
step in the designing of any system is to design the
power supply required for that system .In our project,
we have designed 5V supply according to our need.
@ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 3 | Mar-Apr 2018
Page: 512
International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470
IV. Prototype Implementation:
A. Algorithm:
Step1: Start the program.
Step2: Read the input background image of the empty
road.
Step3: Read the new image with vehicles on road.
Step4: Convert the images to grayscale format using
double precision.
Step5: Find the width and height of the image.
Step6: Set threshold value =
Step7: Find the difference between frames based on
the threshold.
present in the image. After calculating the number of
vehicles we will came to know in which side the
density is high. The time period of green light and red
light is assigned on the basis of the density of the
traffic present at that time.
Automatic Number Plate Recognition (ANPR)
technique offers the ability to find a person who
breaks the Traffic rules and give notice via mobile
phone. This process is done via pressure sensor which
is activated when red signal is ON, whenever any
vehicle crosses Zebra crossing line, sensor gives
signal to digital web camera. Camera can be used to
identify vehicles by reading number plates and use the
information that is stored at the RTO server .Then, the
message is sent to the respective owner of the vehicle
using GSM technique.
C. Result 1:
Step8: If frame diff > than 44, then assign that image
to a variable else “0” if no difference is found.
Step9: Increase the contrast of the output image using
imadjust()
Step10:Find a greythreshold value using graythresh()
command.
Step11: Add Gaussian noise to the output difference.
Step12: Apply Weiner filter to filter the blobs
Step13: Convert to binary image
Step14: Fill holes to the blobs
Step15: Open all blobs having area greater than 5000
Step16: Count the number of cars using bwconncomp
or bwlabel
Step17: Display the output image
Step18: Stop the program
B. Implementation:
The system is designed to develop a vehicle density
based traffic management system. The camera
captures the image of traffic condition at certain
interval of time. Decision is taken by the traffic light
engine depending on the density of vehicles present.
The image captured in the traffic signal is processed
and converted into grayscale image then its threshold
is calculated based on which the contour has been
drawn in order to calculate the number of vehicles
@ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 3 | Mar-Apr 2018
Page: 513
International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470
D. Result 2:
REFERENCES:
1. R.B.Jayanthi Rajee, V. Devika, M. Abarna, A.
Aswini Priya –“Traffic Management System using
Image Processing and ARM Processor”International Journal of Computer Systems (ISSN:
2394-1065), Volume 02– Issue 03, March, 2015.
2. A Ranganath, T Sree Valli “ INTELLIGENT
MANAGEMENT SYSTEM FOR DENSITY
BASED CONTROL, STOLEN VEHICLE AND
AUTO CLEARANCE ”- International Journal of
Advanced Technology in Engineering and
Science,vol no.3-Issue 08, August,2015.
3. Farheena Shaikh, Naisha Taban Khan, Saima
Zareen Ansari “Controlling Traffic Light Signals
to Implement Traffic Scheduling Using Density
Calculation” – International Journal on Recent and
Innovation
Trends
in
computing
and
communication, Volume: 3 Issue: 2 (ISSN: 23218169), September ,2014.
V. Conclusion:
To reduce the congestion and crime an advanced
system is designed here in this project. In the earlier
system, switching of signal at the particular instant of
time. But in our system switching time depend upon
the vehicle density of traffic. The ANPR technique
used to identify vehicles by only their number plates
on Top. ANPR technology tends to be region-specific,
owing to plate variation from place to place.
However, as we have developed, the systems have
become much more accurate and reliable. Using this
technique RTO police can fine the person who
disobey the traffic rule i.e. signal break. We believe
that this may bring a revolutionary change in traffic
management system on its application in its actual
field environment.
4. Mahesh Satpute, Nikhil Nanhe, Ashish Nanda,
Amit Patil and Pradnyashil Kelkar- “Survey on
Intelligent Traffic Signal Management System”
International Journal For Research in Emerging
Science and Technology, Special-Issue-1-Jan2017.
5. Vismay Pandit , Jinesh Doshi, Dhruv Mehta,
Ashay Mhatre and Abhilash Janardhan “Smart
traffic control system using Image Processing ” International Journal of Emerging Trends and
Technology in Computer Science, vol no.3, Issue1, January and February 2014.
@ IJTSRD | Available Online @ www.ijtsrd.com | Volume – 2 | Issue – 3 | Mar-Apr 2018
Page: 514